Computer-based word processing applications, such as speech recognition, grammatical and spelling correction, textual searching, etc., typically employ some form of probabilistic character recognition system, unique to a particular language, to analyze a particular property of a body of text. For an illustration of such computer-based character recognition systems attention may be directed to the following U.S. Patents: Blum et al "Cryptographic Analysis System" U.S. Pat. No. 4,610,025; Balm "Method and Apparatus for Context-Aided Recognition" U.S. Pat. No. 4,058,795; Bokser "Means for Resolving Ambiguities in Text Based Upon Character Context" U.S. Pat. No. 4,754,498; and Baker et al "Speech Recognition Apparatus and Method" U.S. Pat. No. 4,783,803.
Language identification systems, namely, identifying the particular language of a given quantity of speech or text, on the other hand, have been based on an analysis of the characteristics of a speech signal waveform produced by the human voice (often converted into machine readable (digitized) format). Unfortunately, because many of the characteristics of a signal waveform that is representative of human speech is the same or very similar for different languages, the amount of information available to clearly demarcate one spoken language from another is extremely limited and is usually processed through the use of a histogram profile, thereby making the process a time-consuming exercise. For a discussion of phonetic speech processing, attention may be directed to an article entitled "A Phonetically-Based Speech Recognition System" by W. S. Meisel et al, in Speech Technology, Apr/May 1989, pp 44-48.